Authors: Sarah L. Grace,1 Abigail P. Cooley,1 Jennifer A. Bunn2, Paula Parker1
1 Department of Exercise Science, Campbell University, Buies Creek, NC, USA
2 Department of Kinesiology, Sam Houston State University, Huntsville, TX, USA
Paula Parker, Ed.D
PO Box 414,
Buies Creek, NC 27506
Sarah L. Grace is an undergraduate student at Campbell University. She is studying Biology and plans to attend Dental School upon graduation.
Abigail P. Cooley is a recent graduate of Campbell University. She earned her Bachelor of Science in Biomedical Humanities in December 2022 and plans to attend Medical School.
Jennifer A. Bunn, PhD, FACSM, is an Associate Dean in the College of Health Sciences and a faculty member in the Department of Kinesiology at Sam Houston State University. Her areas of research interest include physiological factors affecting female collegiate athlete performance.
Paula Parker, EdD, CMPC, is an Associate Professor and Chair in the Department of Exercise Science at Campbell University. Her areas of research interest include psychological factors affecting female collegiate athlete performance.
Associations between game outcome, game location, and wellness in Division I women’s lacrosse athletes
PURPOSE: Athlete wellness—a subjective measure assessing the response to the previous day’s physiological and psychological stress—has subsequent influence on the day’s performance. Game location (i.e., home, away) is also believed to influence performance and game outcome. The purpose of this study was to determine if game location and game day wellness were related to game outcome for a collegiate women’s lacrosse team. METHODS: Athletes (n = 34) completed a daily subjective wellness survey each morning. The survey consisted of questions related to muscle soreness, sleep quality, stress, and fatigue, with responses rated in arbitrary units (AU) using the anchors of 0, 25, 50, 75, and 100, and higher scores represented positive affect. The scores of each of the four responses were averaged to calculate the overall wellness score. Individual athlete wellness scores were categorized as above or below the team mean for each game. A chi-square analysis was used to evaluate the relationship between the wellness variables and game location with the game outcome. RESULTS: The season consisted of seven losses and nine wins, with 10 games played at an away location and six games played at home. Location was not related to game outcome (p = .152), nor were any of the game day wellness sub-scores or composite score (wellness: 71.4 ± 2.7 AU, p = .614; muscle soreness: 63.8 ± 2.9 AU, p = .527; sleep: 83.0 ± 3.4 AU, p = .527; energy: 80.0 ± 1.5 AU, p = .490; stress: 65.0 ± 4.7 AU, p = .490). CONCLUSIONS: Game location, and game day wellness were not related to game outcome in Division I women’s lacrosse athletes. These findings refute previous beliefs regarding the importance of “home field advantage.” Further exploration regarding sleep quality differences in relation to game location and subsequent game outcome are warranted. APPLICATION IN SPORT: Coaches and athletes can use this information to refute previously believed notions about advantages to playing home games. Coaches can work with their athletes to ensure similar pre-game preparation on and off the field for optimal performance.
Wellness is a subjective measure indicating an athlete’s response to training volume and perceptions of individual readiness for training (7). It considers both physiological and psychological factors among the athletes as they train and compete. Athlete wellness is influenced by various stressors acting together and placing physical and psychological demands on them (13). Wellness has been shown to increase after a win, as players had improved sleep quality, decreased stress, and decreased fatigue (8). However, following a loss, athletes felt their sleep quality decreased, with stress and fatigue high (8).
As student-athletes face pressures from their sport, the classroom, and other extracurriculars, they can experience higher levels of stress (5, 6, 14, 18, 27, 28). A 2022 report by the NCAA, for example, showed student athletes were reporting mental health concerns 1.5 to 2 times higher than data reported before 2020. During the COVID-19 pandemic, these concerns included mental exhaustion, sleep difficulties, anxiety, and hopelessness, with female student-athletes reporting higher scores than male student-athletes in all categories (21).
General categories of stress include emotional, mental, and physical, with each type potentially triggering adverse effects on the athletes and their athletic performance. In a study of collegiate lacrosse athletes, Crouch et al. (2021) found subjects with perceptually less stress who scored higher on sleep quality ratings ran approximately 300 meters more on the day, with approximately 70 of those meters coming from >60% of maximum sprint speed (7). Student-athletes determined to have lower stress also logged higher speeds on a sprint test and moved 3.5 meters more on the day for every one-point increase in their overall wellness score measured by a VX Sport smart phone application (Wellington, New Zealand) that assessed energy levels, muscle soreness, sleep quality, and stress levels. Limited research has been conducted on psychological factors (e.g., wellness) specific to women’s collegiate athletes; however, published studies on other athletic populations have indicated that improved wellness leads to improved athletic performance (7, 10, 13, 16, 17).
Game location has been shown to influence athletes and game outcomes as well (12). A study consisting of 126 close games (goal differences of 1.98 ± 1.37) from the Spanish Professional Men’s Handball League indicated that home teams outperformed their opponents in terms of instrumentality, aggressive behavior (i.e., behavior aggressive enough to facilitate obtaining a victory), shots blocked, and successful defensive actions and anticipations that generated turnovers (12). Studies evaluating game location and game outcome in professional athletes showed the home team had a significant advantage over the away team with a higher home team winning percentage (22) and higher offensive-based statistics (24). In the English Premier League, home field advantage was linked with improved offense-based statistics including reaching the opponent’s box more frequently and getting more shots off passes. Although these details are not always reflected in the final score, these factors still give the home team a competitive edge (24). In professional sports in the United States, home team advantages were related to having a higher winning percentage (55.5%) compared to away teams (25). Thus, previous studies show that game location is an indicator of athletic performance and game outcome.
To date, literature has explored the influence of athlete wellness and readiness on individual performance and the role of game location on game outcome, but the concepts—wellness and game location—have not yet been joined to evaluate their relationship with game outcome. The purpose of this study was to determine if game location and game day wellness were related to game outcome for a collegiate women’s lacrosse team. It was hypothesized that both game location and game day wellness were related to game outcome. Specifically, it was expected that high game day wellness will be noted for wins compared to losses and that wins will be linked to the team’s home location.
This study was a prospective observational design and athletes were observed during the spring 2022 competitive season. Participants included Division I female lacrosse athletes. Wellness was evaluated daily through the VX Sport Cloud system (Wellington, New Zealand) and game locations and outcomes were publicly available data. This study was approved by the institutional review board and conducted in conjunction with the Declaration of Helsinki.
The participants of this study included female Division I varsity women’s lacrosse athletes (n = 34). The players were monitored during in-season training and competition. Players provided consent prior to the start of the study. Athletes were excluded from analyses if they were injured and missed more than 40% of the games (n = 2).
Athletes completed a subjective online questionnaire (VX Sport Cloud platform, Wellington, New Zealand) each morning prior to 10:30 am to rate their overall wellness. The survey consisted of four questions related to muscle soreness, sleep quality, stress, and fatigue. Each question was rated in arbitrary units (AU) using the anchors of 0, 25, 50, 75, and 100, with higher scores representing better wellness. Each of the four subscores was averaged to calculate the overall wellness score. These wellness questions and data collection methods were the same as those evaluated by Crouch et al. (2021) and Frick et al. (2021) to align with recent lacrosse literature (7, 9). Although wellness questionnaires such as the one used in the present study may lack experimental validity (26), they are often used and trusted by sport performance practitioners and have practical validity as seen by their use in other research studies (5, 6, 10, 11, 14, 18, 19). Each athlete’s wellness score and subscores from game days were used for analyses. The team mean of each score was calculated, and individual athlete wellness scores from the game day were categorized as above or below the team mean for each game to indicate a high- versus a low-wellness score day.
Game locations and outcomes for the 2022 season were obtained from a publicly available website (4). The team competed in 17 games during the season, but one game was removed from analysis because it was played at a neutral site and was considered as neither home nor away. Of the 16 games analyzed, seven (43.8%) were losses and nine (56.3%) were wins, and six (375.5%) were played at the team’s home field and ten (62.5%) were played away.
The mean and standard deviation of each wellness metric for game day were calculated. A chi-square analysis was used to evaluate the relationship of game outcome (win versus loss) with game location (home versus away) and high versus low wellness scores. An alpha level of .05 was used to determine significance.
The mean wellness scores on game day were 71.4 ± 2.7 AU for overall wellness, 63.8 ± 2.9 AU for muscle soreness, 83.0 ± 3.4 AU for sleep quality, 80.0 ± 1.5 AU for energy, and 65.0 4.7 AU for stress. These were the values used to determine above average or below average wellness scores for the chi-square analyses.
Table 1 shows the cross-tabulations of game location, wellness, and outcome. Game location did not have any association with game outcome (χ2(1) = 2.049, p = 0.152). The results showed that 42.9% of the losses occurred at away games and 57.1% of losses occurred at home. For wins, 77.8% of the wins happened on the road and only 22.2% of the wins occurred at home games.
None of the game-day wellness variables showed any relationship with game outcome either: overall wellness (χ2(1) = 0.254, p = 0.614), muscle soreness (χ2(1) = 0.400, p = 0.527), sleep quality (χ2(1) = 0.400, p = 0.527), energy (χ2(1) = 0.473, p = 0.490), and stress (χ2(1) = 0.476, p = 0.490). For the wellness composite score, 57.1% of the losses occurred on low wellness days and 42.9% of losses occurred on high wellness days. For wins, 44.4% came on low wellness days and 55.6% occurred on high wellness days. With muscle soreness, 37.5% of losses occurred with low muscle soreness scores (poor affect) and 66.7% of losses occurred with high muscle soreness scores (positive affect). The wins showed that 62.5% occurred with low muscle soreness scores and 37.5% occurred with high muscle soreness scores. For sleep, 60% of losses occurred with low sleep quality and 40% occurred with high sleep quality. Low sleep quality was associated with 40% of wins and high sleep quality was associated with 60% of the wins. Low energy scores were associated with 60% of the losses and 80% of the wins. Whereas high energy scores were associated with 40% of the losses and only 20% of the wins. Low stress scores (negative affect) were associated with 40% of the losses and 20% of the wins. High stress scores (positive affect) were associated with 60% of the losses and 80% of the wins.
This study aimed to evaluate the relationship of game day wellness and game location with game outcome. There was no relationship between any of these factors and game outcome. These results contradict the hypothesis and previous research that home teams have a significant advantage over away teams (24) and that higher stress levels and thus decreased wellness in collegiate athletes has adverse effects on athletic performance (7).
The winning percentage was lower as a home team in this study with 77.8% of the wins at away games. While the results of this study were not significant, it is noteworthy as we examine the impact of game location on game outcome. In a meta-analysis of 30 research studies by Jamieson (2010), it was determined the home team is expected to win 60% of the time (15). A more recent 2022 study examining offensive statistics in English Premier League soccer also showed the home team has an advantage over the away team with a higher home team winning (24). The results for the collegiate lacrosse players in the current study, however, indicate that the team had a higher winning percentage as an away team. All except one of the away wins were over teams who were ranked lower in the ratings power index (RPI), meaning these were lower quality teams. The team of study won one game over a higher quality team, and this occurred at an away location. Two home losses and one away loss occurred to lower quality teams, and four losses—two home and two away—were against teams ranked higher in the RPI. These data align with previous literature in collegiate women’s lacrosse (27) and soccer (22) suggesting that the quality of the opponent has a strong relationship to the game outcome.
Regarding wellness, 55.5% of wins from the 2022 season came with high wellness days while 57.1% of the losses came with low wellness days. Thus, wellness was not related to game outcome for the Division I female lacrosse athletes. Crouch et al. (2021) found that overall wellness was an indicator of external training load metrics, with athletes moving more for every one-point increase in wellness (7). Bynum et al. (2022) also showed that the total distance run by attackers and midfielders had a moderate correlation with goals scored (3). Collectively, these two studies suggest that high wellness scores would correlate with greater total distance and therefore more goals scored. However, despite the performance improvements of a high wellness score, the results of the present study indicate that wellness does not translate to the game outcome. Wellness may not translate to game outcome because the goal of training is to reduce the volume as the team approaches a game in the schedule, thereby enhancing recovery and wellness. Wellness scores in professional athletes fluctuate with each game microcycle, showing a sharp drop after a game with a progressive daily increase in preparation for the next game (10). This drop in wellness may be what the athletes experienced in the present study as there was little variation in the overall wellness scores (± 2.7 AU) on game days. The intended preparation to improve overall wellness for game day may therefore have rendered wellness useless in exploring its relationship with game outcome.
The wellness sub-scores showed no relationship with game outcome, but there is relevant information for performance from these sub-scores. Crouch et al. (2021) showed that sleep quality and energy were the most informative sub-scores in predicting external training load metrics and that higher self-reported sleep quality resulted in greater performance output (7). During the 2022 season, 60% of wins came with high sleep quality and 60% of losses came with low sleep quality. While not statistically supported, the results of the present study do support the notion that sleep is important for successful performance. Regarding stress, studies show that added stressors can lead to increased fatigue and have an impact on overall wellness, thus decreasing athletic performance and increasing risk of injury (22). Eighty percent of the 2022 wins came when stress scores were high, supporting the concept that performance may be improved with lower feelings of stress. The effect of energy on collegiate athletic performance has not been heavily studied, but Crouch et al. (2021) found that higher self-reported energy was associated with greater performance (7). The present study showed little variance in game-day energy scores and no association between energy and game outcome. Previous literature indicates that muscle soreness had no relation with training volume or session ratings of perceived exertion (7) and the current study also shows no relationship between muscle soreness and game outcome. Each of the four sub-scores—muscle soreness, sleep quality, energy, and stress—have different implications in overall wellness and thus athletic performance and exertion.
Some limitations encountered with this study are that these data were collected from only one team across one season. Conducting the study over multiple seasons rather than one season would increase the accuracy of the findings and increase the sample size. Further study of psychological factors in collegiate athletes and their impact on game outcome is warranted. Investigating the impact of sleep quality differences in relation to game location and game outcome is a possible future direction for further studies.
The results of this study are not consistent with previous research and did not support our hypothesis as neither game location nor wellness were related to game outcome. Based on the results, the team had an advantage as an away team rather than as a home team, and game outcome was not impacted by wellness. Game outcome in Division I women’s lacrosse is likely more associated with team rank and matchups, rather than location and athlete wellness. The conclusion may be drawn that game location and athlete wellness do not predict game results which refutes previous beliefs. While these results do not support previous studies, they are notable as we aim to expand knowledge on these factors that have not yet been heavily studied in collegiate athletes.
APPLICATION TO SPORT
From the current research, coaches and athletes are encouraged to prioritize sleep quality with their athletes leading into a game. Astridge found 42% of student-athletes reported regular poor sleep with other research finding adolescent student-athletes who averaged less than eight hours of sleep per night were 1.7 times more likely to experience an injury (1, 20). Improving sleep quality includes maintaining good sleep hygiene with reduced exposure to blue light prior to bedtime, following similar bedtime preparatory routines and times, and creating a healthy sleeping environment specific to one’s preferences for darkness, temperature, and noise (23). These positive sleep habits should be encouraged prior to games, whether at home or away. Furthermore, coaches can inform their athletes that location likely has little to do with the game outcome.
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